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errors fixed

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Ricardo 2013-09-13 12:25:53 +01:00
parent b739a10562
commit 1b54365f7c
1 changed files with 7 additions and 9 deletions
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16
GPy/testing/unit_tests.py
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@ -166,10 +166,7 @@ class GradientTests(unittest.TestCase):
X = np.hstack([np.random.normal(5, 2, N / 2), np.random.normal(10, 2, N / 2)])[:, None]
Y = np.hstack([np.ones(N / 2), np.zeros(N / 2)])[:, None]
kernel = GPy.kern.rbf(1)
distribution = GPy.likelihoods.likelihood_functions.Binomial()
likelihood = GPy.likelihoods.EP(Y, distribution)
m = GPy.core.GP(X, likelihood, kernel)
m.ensure_default_constraints()
m = GPy.models.GPClassification(X,Y,kernel=kernel)
m.update_likelihood_approximation()
self.assertTrue(m.checkgrad())
@ -179,10 +176,11 @@ class GradientTests(unittest.TestCase):
Y = np.hstack([np.ones(N / 2), np.zeros(N / 2)])[:, None]
Z = np.linspace(0, 15, 4)[:, None]
kernel = GPy.kern.rbf(1)
distribution = GPy.likelihoods.likelihood_functions.Binomial()
likelihood = GPy.likelihoods.EP(Y, distribution)
m = GPy.core.SparseGP(X, likelihood, kernel, Z)
m.ensure_default_constraints()
m = GPy.models.SparseGPClassification(X,Y,kernel=kernel,Z=Z)
#distribution = GPy.likelihoods.likelihood_functions.Binomial()
#likelihood = GPy.likelihoods.EP(Y, distribution)
#m = GPy.core.SparseGP(X, likelihood, kernel, Z)
#m.ensure_default_constraints()
m.update_likelihood_approximation()
self.assertTrue(m.checkgrad())
@ -191,7 +189,7 @@ class GradientTests(unittest.TestCase):
X = np.hstack([np.random.rand(N / 2) + 1, np.random.rand(N / 2) - 1])[:, None]
k = GPy.kern.rbf(1) + GPy.kern.white(1)
Y = np.hstack([np.ones(N/2),np.zeros(N/2)])[:,None]
m = GPy.models.FITCClassification(X, Y=Y)
m = GPy.models.FITCClassification(X, Y, kernel = k)
m.update_likelihood_approximation()
self.assertTrue(m.checkgrad())